From e2ce457b4bb5ecbe4fde5c845584e32466c5c9a0 Mon Sep 17 00:00:00 2001
From: "louis.heraut" <louis.heraut@inrae.fr>
Date: Thu, 25 Nov 2021 18:59:02 +0100
Subject: [PATCH] Plot aes matrix
---
plotting/panel.R | 433 ++++++++++++++++-------------------------
processing/extractBH.R | 36 ++++
processing/extractNV.R | 38 +++-
script.R | 50 ++---
4 files changed, 266 insertions(+), 291 deletions(-)
diff --git a/plotting/panel.R b/plotting/panel.R
index d7d458e..49642ea 100644
--- a/plotting/panel.R
+++ b/plotting/panel.R
@@ -10,216 +10,7 @@ library(ggh4x)
library(RColorBrewer)
-# Time panel
-panel = function (df_data, df_meta, layout_matrix, figdir='', filedir_opt='', filename_opt='', variable='', df_trend=NULL, p_threshold=0.1, unit2day=365.25, type='', period=NULL, missRect=FALSE, time_header=NULL, info_header=TRUE, header_ratio=2) {
-
- if (all(class(df_data) != 'list')) {
- df_data = list(df_data)
- }
-
- nbp = length(df_data)
-
- if (all(class(df_trend) != 'list')) {
- df_trend = list(df_trend)
- if (length(df_trend) == 1) {
- df_trend = replicate(nbp, df_trend)
- }}
-
- if (all(class(p_threshold) != 'list')) {
- p_threshold = list(p_threshold)
- if (length(p_threshold) == 1) {
- p_threshold = replicate(nbp, p_threshold)
- }}
-
- if (all(class(unit2day) != 'list')) {
- unit2day = list(unit2day)
- if (length(unit2day) == 1) {
- unit2day = replicate(nbp, unit2day)
- }}
-
- if (all(class(type) != 'list')) {
- type = list(type)
- if (length(type) == 1) {
- type = replicate(nbp, type)
- }}
-
- if (all(class(missRect) != 'list')) {
- missRect = list(missRect)
- if (length(missRect) == 1) {
- missRect = replicate(nbp, missRect)
- }}
-
- list_df2plot = vector(mode='list', length=nbp)
- minTrend = c()
- maxTrend = c()
- nokTrend = c()
-
- for (i in 1:nbp) {
-
- df2plot = list(data=df_data[[i]],
- trend=df_trend[[i]],
- p_threshold=p_threshold[[i]],
- unit2day=unit2day[[i]],
- type=type[[i]],
- missRect=missRect[[i]])
-
- okTrend = df_trend[[i]]$p[df_trend[[i]]$p <= p_threshold[[i]]]
-
- print(okTrend)
-
- minTrend[i] = min(okTrend, na.rm=TRUE)
- maxTrend[i] = max(okTrend, na.rm=TRUE)
- nokTrend[i] = length(okTrend)
-
- list_df2plot[[i]] = df2plot
- }
-
-
- outfile = "Panels"
- if (filename_opt != '') {
- outfile = paste(outfile, '_', filename_opt, sep='')
- }
- outfile = paste(outfile, '.pdf', sep='')
-
- # If there is not a dedicated figure directory it creats one
- outdir = file.path(figdir, filedir_opt, sep='')
- if (!(file.exists(outdir))) {
- dir.create(outdir)
- }
-
- outdirTmp = file.path(outdir, 'tmp')
- if (!(file.exists(outdirTmp))) {
- dir.create(outdirTmp)
- }
-
-
- # Get all different stations code
- Code = levels(factor(df_meta$code))
- nCode = length(Code)
-
- for (code in Code) {
-
- # Print code of the station for the current plotting
- print(paste("Plotting for sation :", code))
-
- nbh = as.numeric(info_header) + as.numeric(!is.null(time_header))
- nbg = nbp + nbh
-
- P = vector(mode='list', length=nbg)
-
- if (info_header) {
- Htext = text_panel(code, df_meta)
- P[[1]] = Htext
- }
-
- if (!is.null(time_header)) {
- time_header_code = time_header[time_header$code == code,]
-
- Htime = time_panel(time_header_code, df_trend_code=NULL,
- period=period, missRect=TRUE,
- unit2day=365.25, type='Q')
-
- P[[2]] = Htime
- }
-
-
- nbcol = ncol(as.matrix(layout_matrix))
- for (i in 1:nbp) {
- df_data = list_df2plot[[i]]$data
- df_trend = list_df2plot[[i]]$trend
- p_threshold = list_df2plot[[i]]$p_threshold
- unit2day = list_df2plot[[i]]$unit2day
- missRect = list_df2plot[[i]]$missRect
- type = list_df2plot[[i]]$type
-
- df_data_code = df_data[df_data$code == code,]
- df_trend_code = df_trend[df_trend$code == code,]
-
- if (df_trend_code$p <= p_threshold){
- color_res = get_color(df_trend_code$p,
- minTrend[i],
- maxTrend[i],
- ncolor=10,
- palette_name="RdYlBu",
- reverse=TRUE)
-
- color = color_res$color
- palette = color_res$palette
-
- } else {
- color = NULL
- palette = NULL
- }
-
- print(paste('min', minTrend[i]))
- print(df_trend_code$p)
- print(paste('max', maxTrend[i]))
-
- if (i == 1) {print(palette)}
-
- print(paste('color', color))
- print("")
-
- p = time_panel(df_data_code, df_trend_code, type=type,
- p_threshold=p_threshold, missRect=missRect,
- unit2day=unit2day, last=(i > nbp-nbcol),
- color=color)
-
- P[[i+nbh]] = p
- }
-
- layout_matrix = as.matrix(layout_matrix)
- nel = nrow(layout_matrix)*ncol(layout_matrix)
-
- ##
- idNA = which(is.na(layout_matrix), arr.ind=TRUE)
-
- layout_matrix[idNA] = seq(max(layout_matrix, na.rm=TRUE) + 1,
- max(layout_matrix, na.rm=TRUE) + 1 +
- nel)
- ##
-
- layout_matrix_H = layout_matrix + nbh
-
-
- LM = c()
- LMcol = ncol(layout_matrix_H)
- LMrow = nrow(layout_matrix_H)
- for (i in 1:(LMrow+nbh)) {
-
- if (i <= nbh) {
- LM = rbind(LM, rep(i, times=LMcol))
- } else {
- LM = rbind(LM,
- matrix(rep(layout_matrix_H[i-nbh,],
- times=header_ratio),
- ncol=LMcol, byrow=TRUE))
- }}
-
- plot = grid.arrange(grobs=P, layout_matrix=LM)
-
- # plot = grid.arrange(rbind(cbind(ggplotGrob(P[[2]]), ggplotGrob(P[[2]])), cbind(ggplotGrob(P[[3]]), ggplotGrob(P[[3]]))), heights=c(1/3, 2/3))
-
-
- # Saving
- ggsave(plot=plot,
- path=outdirTmp,
- filename=paste(as.character(code), '.pdf', sep=''),
- width=21, height=29.7, units='cm', dpi=100)
-
- }
-
- pdf_combine(input=file.path(outdirTmp, list.files(outdirTmp)),
- output=file.path(outdir, outfile))
- unlink(outdirTmp, recursive=TRUE)
-}
-
-
-
-
-
-
-time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missRect=FALSE, unit2day=365.25, period=NULL, norm=TRUE, last=FALSE, color=NULL) {
+time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missRect=FALSE, unit2day=365.25, period=NULL, last=FALSE, color=NULL) {
if (type == 'sqrt(Q)') {
@@ -238,33 +29,31 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR
}
dbrk = 10^power
- ### /!\ PROBLÈME entre 11 et 10 ###
- if (norm) {
- df_data_code$Qm3s = df_data_code$Qm3s / dbrk
-
- if (!is.null(df_trend_code)) {
- df_trend_code$p = df_trend_code$p / dbrk
- df_trend_code$intercept = df_trend_code$intercept / dbrk
- }
+ df_data_code$Qm3sN = df_data_code$Qm3s / dbrk
- maxQ = max(df_data_code$Qm3s, na.rm=TRUE)
+ if (!is.null(df_trend_code)) {
- if (maxQ >= 5) {
- dbrk = 1.0
- accuracy = 0.1
- } else if (maxQ < 5 & maxQ >= 3) {
- dbrk = 0.5
- accuracy = 0.1
- } else if (maxQ < 3 & maxQ >= 2) {
- dbrk = 0.4
- accuracy = 0.1
- } else if (maxQ < 2 & maxQ >= 1) {
- dbrk = 0.2
- accuracy = 0.1
- } else if (maxQ < 1) {
- dbrk = 0.1
- accuracy = 0.1
- }
+ df_trend_code$trendN = df_trend_code$trend / dbrk
+ df_trend_code$interceptN = df_trend_code$intercept / dbrk
+ }
+
+ maxQN = max(df_data_code$Qm3sN, na.rm=TRUE)
+
+ if (maxQN >= 5) {
+ dbrk = 1.0
+ accuracy = 0.1
+ } else if (maxQN < 5 & maxQN >= 3) {
+ dbrk = 0.5
+ accuracy = 0.1
+ } else if (maxQN < 3 & maxQN >= 2) {
+ dbrk = 0.4
+ accuracy = 0.1
+ } else if (maxQN < 2 & maxQN >= 1) {
+ dbrk = 0.2
+ accuracy = 0.1
+ } else if (maxQN < 1) {
+ dbrk = 0.1
+ accuracy = 0.1
}
dDate = as.numeric(df_data_code$Date[length(df_data_code$Date)] -
@@ -286,8 +75,6 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR
p = ggplot() +
# theme_bw() +
-
- ggtitle(bquote(.(type)~' ['*m^{3}*'.'*s^{-1}*'] x'~10^{.(as.character(power))})) +
theme(panel.background=element_rect(fill='white'),
text=element_text(family='sans'),
@@ -325,19 +112,19 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR
if (type == 'sqrt(Q)' | type == 'Q') {
p = p +
- geom_line(aes(x=df_data_code$Date, y=df_data_code$Qm3s),
+ geom_line(aes(x=df_data_code$Date, y=df_data_code$Qm3sN),
color='grey20',
size=0.3)
} else {
p = p +
- # geom_line(aes(x=df_data_code$Date, y=df_data_code$Qm3s),
+ # geom_line(aes(x=df_data_code$Date, y=df_data_code$Qm3sN),
# color='grey70') +
- geom_point(aes(x=df_data_code$Date, y=df_data_code$Qm3s),
+ geom_point(aes(x=df_data_code$Date, y=df_data_code$Qm3sN),
shape=1, color='grey20', size=1)
}
if (missRect) {
- NAdate = df_data_code$Date[is.na(df_data_code$Qm3s)]
+ NAdate = df_data_code$Date[is.na(df_data_code$Qm3sN)]
dNAdate = diff(NAdate)
NAdate_Down = NAdate[append(Inf, dNAdate) != 1]
NAdate_Up = NAdate[append(dNAdate, Inf) != 1]
@@ -346,8 +133,8 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR
geom_rect(aes(xmin=NAdate_Down,
ymin=0,
xmax=NAdate_Up,
- ymax=maxQ*1.1),
- linetype=0, fill='Wheat', alpha=0.3)
+ ymax=maxQN*1.1),
+ linetype=0, fill='Wheat', alpha=0.4)
}
if ((type == 'sqrt(Q)' | type == 'Q') & !is.null(period)) {
@@ -356,13 +143,13 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR
geom_rect(aes(xmin=min(df_data_code$Date),
ymin=0,
xmax=period[1],
- ymax= maxQ*1.1),
+ ymax= maxQN*1.1),
linetype=0, fill='grey85', alpha=0.3) +
geom_rect(aes(xmin=period[2],
ymin=0,
xmax=max(df_data_code$Date),
- ymax= maxQ*1.1),
+ ymax= maxQN*1.1),
linetype=0, fill='grey85', alpha=0.3)
}
@@ -374,19 +161,31 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR
abs_num = as.numeric(abs) / unit2day
- ord = abs_num * df_trend_code$trend +
- df_trend_code$intercept
+ ord = abs_num * df_trend_code$trendN +
+ df_trend_code$interceptN
if (!is.null(color)) {
p = p +
geom_line(aes(x=abs, y=ord),
- color=color)
+ color=color,
+ size=0.7)
} else {
p = p +
geom_line(aes(x=abs, y=ord),
color='cornflowerblue')
}
- }}
+
+ p = p +
+ ggtitle(bquote(.(type)~~'['*m^{3}*'.'*s^{-1}*'] x'~10^{.(as.character(power))}~~~'tendance :'~.(format(df_trend_code$trend, scientific=TRUE, digits=3))~m^{3}*'.'*s^{-1}*'.'*an^{-1}))
+
+ } else {
+ p = p +
+ ggtitle(bquote(.(type)~' ['*m^{3}*'.'*s^{-1}*'] x'~10^{.(as.character(power))}))
+ }
+ } else {
+ p = p +
+ ggtitle(bquote(.(type)~' ['*m^{3}*'.'*s^{-1}*'] x'~10^{.(as.character(power))}))
+ }
# if (norm) {
@@ -410,8 +209,8 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR
max(df_data_code$Date)),
expand=c(0, 0)) +
- scale_y_continuous(breaks=seq(0, maxQ*10, dbrk),
- limits=c(0, maxQ*1.1),
+ scale_y_continuous(breaks=seq(0, maxQN*10, dbrk),
+ limits=c(0, maxQN*1.1),
expand=c(0, 0),
labels=label_number(accuracy=accuracy))
@@ -425,7 +224,7 @@ text_panel = function(code, df_meta) {
text = paste(
"<span style='font-size:18pt'> station <b>", code, "</b></span><br>",
"nom : ", df_meta_code$nom, "<br>",
- "territoire : ", df_meta_code$territoire, "<br>",
+ "région hydrographique : ", df_meta_code$region_hydro, "<br>",
"position : (", df_meta_code$L93X, "; ", df_meta_code$L93Y, ")", "<br>",
"surface : ", df_meta_code$surface_km2, " km<sup>2</sup>",
sep='')
@@ -440,28 +239,104 @@ text_panel = function(code, df_meta) {
-get_color = function (value, min, max, ncolor, palette_name="RdYlBu", reverse=TRUE) {
-
- if (min == max) {
- palette = colorRampPalette(brewer.pal(11, palette_name))(3)
- color = palette[2]
- return(list(color=color, palette=c(color)))
+matrice_panel = function (list_df2plot, df_meta) {
+
+ nbp = length(list_df2plot)
+
+ minTrend = c()
+ maxTrend = c()
+
+ for (i in 1:nbp) {
+
+ df_trend = list_df2plot[[i]]$trend
+ p_threshold = list_df2plot[[i]]$p_threshold
+
+ okTrend = df_trend$trend[df_trend$p <= p_threshold]
+
+ minTrend[i] = min(okTrend, na.rm=TRUE)
+ maxTrend[i] = max(okTrend, na.rm=TRUE)
+ }
+
+ # Get all different stations code
+ Code = levels(factor(df_meta$code))
+
+ Type_mat = c()
+ Code_mat = c()
+ Color_mat = c()
+
+ for (code in Code) {
+
+ for (i in 1:nbp) {
+ df_trend = list_df2plot[[i]]$trend
+ p_threshold = list_df2plot[[i]]$p_threshold
+ type = list_df2plot[[i]]$type
+
+ Type_mat[i] = as.character(type)
+ Code_mat[i] = code
+
+ df_trend_code = df_trend[df_trend$code == code,]
+
+ if (df_trend_code$p <= p_threshold){
+ color_res = get_color(df_trend_code$trend,
+ minTrend[i],
+ maxTrend[i],
+ palette_name='perso',
+ reverse=FALSE)
+
+ color = color_res$color
+
+ } else {
+ color = 'white'
+ }
+
+ Color_mat[i] = color
+ }
}
+
+ mat = ggplot() +
+ geom_tile(aes(x=Type_mat, y=Code_mat, fill=Color_mat))
+
+ return (mat)
+}
+
+
- palette = colorRampPalette(brewer.pal(11, palette_name))(ncolor)
+
+
+get_color = function (value, min, max, ncolor=256, palette_name='perso', reverse=FALSE) {
+
+ if (palette_name == 'perso') {
+ palette = colorRampPalette(c(
+ '#1a4157',
+ '#00af9d',
+ '#fbdd7e',
+ '#fdb147',
+ '#fd4659'
+ ))(ncolor)
+
+ } else {
+ palette = colorRampPalette(brewer.pal(11, palette_name))(ncolor)
+ }
if (reverse) {
palette = rev(palette)
}
- idNorm = (value - min) / (max - min)
-
- id = round(idNorm*(ncolor-1) + 1, 0)
+ palette_cold = palette[1:as.integer(ncolor/2)]
+ palette_hot = palette[(as.integer(ncolor/2)+1):ncolor]
- print(idNorm)
- print(id)
+ ncolor_cold = length(palette_cold)
+ ncolor_hot = length(palette_hot)
- color = palette[id]
+ if (value < 0) {
+ idNorm = (value - min) / (0 - min)
+ id = round(idNorm*(ncolor_cold - 1) + 1, 0)
+ color = palette_cold[id]
+ } else {
+ idNorm = (value - 0) / (max - 0)
+ id = round(idNorm*(ncolor_hot - 1) + 1, 0)
+ color = palette_hot[id]
+ }
return(list(color=color, palette=palette))
}
@@ -480,3 +355,31 @@ void = ggplot() + geom_blank(aes(1,1)) +
axis.ticks = element_blank(),
axis.line = element_blank()
)
+
+
+
+palette_tester = function () {
+
+ n = 300
+ X = 1:n
+ Y = rep(0, times=n)
+
+ palette = colorRampPalette(c(
+ '#1a4157',
+ '#00af9d',
+ '#fbdd7e',
+ '#fdb147',
+ '#fd4659'
+ ))(n)
+
+ p = ggplot() +
+ geom_line(aes(x=X, y=Y), color=palette[X], size=10) +
+ scale_y_continuous(expand=c(0, 0))
+
+ ggsave(plot=p,
+ path='/figures',
+ filename=paste('palette_test', '.pdf', sep=''),
+ width=10, height=10, units='cm', dpi=100)
+}
+
+# palette_teste()
diff --git a/processing/extractBH.R b/processing/extractBH.R
index 93e21ef..2ce4f4b 100644
--- a/processing/extractBH.R
+++ b/processing/extractBH.R
@@ -49,6 +49,40 @@ iQHE = c('0'='qualit
'2'='qualité hautes eaux douteuse')
+iRegHydro = c('D'='Affluents du Rhin',
+ 'E'="Fleuves côtiers de l'Artois-Picardie",
+ 'A'='Rhin',
+ 'B'='Meuse',
+ 'F'='Seine aval (Marne incluse)',
+ 'G'='Fleuves côtiers haut normands',
+ 'H'='Seine amont',
+ 'I'='Fleuves côtiers bas normands',
+ 'J'='Bretagne',
+ 'K'='Loire',
+ 'L'='Loire',
+ 'M'='Loire',
+ 'N'='Fleuves côtiers au sud de la Loire',
+ 'O'='Garonne',
+ 'P'='Dordogne',
+ 'Q'='Adour',
+ 'R'='Charente',
+ 'S'="Fleuves côtiers de l'Adour-Garonne",
+ 'U'='Saône',
+ 'V'='Rhône',
+ 'W'='Isère',
+ 'X'='Durance',
+ 'Y'='Fleuves côtiers du Rhône-Méditérannée et Corse',
+ 'Z'='Îles',
+ '1'='Guadeloupe',
+ '2'='Martinique',
+ '5'='Guyane',
+ '6'='Guyane',
+ '7'='Guyane',
+ '8'='Guyane',
+ '9'='Guyane',
+ '4'='Réunion')
+
+
# Get the selection of data from the 'Liste-station_RRSE' file and the BanqueHydro directory
get_selection = function (computer_data_path, listdir, listname,
cnames=c('code','station', 'BV_km2', 'axe_principal_concerne', 'longueur_serie', 'commentaires', 'choix'),
@@ -190,6 +224,8 @@ extractBH_meta = function (computer_data_path, filedir, filename, verbose=TRUE)
source='BH'
)
+ df_meta$region_hydro = iRegHydro[substr(df_meta$code, 1, 1)]
+
return (df_meta)
} else {
diff --git a/processing/extractNV.R b/processing/extractNV.R
index 8bf6c24..012084e 100644
--- a/processing/extractNV.R
+++ b/processing/extractNV.R
@@ -3,6 +3,40 @@ library(tools)
library(dplyr)
+iRegHydro = c('D'='Affluents du Rhin',
+ 'E'="Fleuves côtiers de l'Artois-Picardie",
+ 'A'='Rhin',
+ 'B'='Meuse',
+ 'F'='Seine aval (Marne incluse)',
+ 'G'='Fleuves côtiers haut normands',
+ 'H'='Seine amont',
+ 'I'='Fleuves côtiers bas normands',
+ 'J'='Bretagne',
+ 'K'='Loire',
+ 'L'='Loire',
+ 'M'='Loire',
+ 'N'='Fleuves côtiers au sud de la Loire',
+ 'O'='Garonne',
+ 'P'='Dordogne',
+ 'Q'='Adour',
+ 'R'='Charente',
+ 'S'="Fleuves côtiers de l'Adour-Garonne",
+ 'U'='Saône',
+ 'V'='Rhône',
+ 'W'='Isère',
+ 'X'='Durance',
+ 'Y'='Fleuves côtiers du Rhône-Méditérannée et Corse',
+ 'Z'='Îles',
+ '1'='Guadeloupe',
+ '2'='Martinique',
+ '5'='Guyane',
+ '6'='Guyane',
+ '7'='Guyane',
+ '8'='Guyane',
+ '9'='Guyane',
+ '4'='Réunion')
+
+
# Extraction of metadata
extractNVlist_meta = function (computer_data_path, filedir, listdir, listname, verbose=TRUE) {
@@ -57,7 +91,7 @@ extractNVlist_meta = function (computer_data_path, filedir, listdir, listname, v
altitude_m=df_meta$Alt,
file_path=file.path(dir_path,
paste(df_meta$CODE, '.txt', sep='')),
- source='NV'
+ source='NV',
)
df_meta = bind_rows(df_meta,
@@ -68,6 +102,8 @@ extractNVlist_meta = function (computer_data_path, filedir, listdir, listname, v
sep=''))))
df_meta = df_meta[order(df_meta$code),]
+
+ df_meta$region_hydro = iRegHydro[substr(df_meta$code, 1, 1)]
} else {
print(paste('filename', list_path, 'do not exist'))
diff --git a/script.R b/script.R
index 9950023..93ba19f 100644
--- a/script.R
+++ b/script.R
@@ -77,7 +77,7 @@ source('processing/extractNV.R', encoding='latin1')
source('processing/format.R', encoding='latin1')
source('processing/analyse.R', encoding='latin1')
source('plotting/panel.R', encoding='latin1')
-# source('plotting/layout.R')
+source('plotting/layout.R', encoding='latin1')
# Usefull library
@@ -155,31 +155,31 @@ res_VCN10trend = get_VCN10trend(df_data, df_meta, period)
# TIME PANEL #
# Plot time panel of debit by stations
-# panel(list(df_data, df_data),
-# layout_matrix=c(1, 2),
-# df_meta=df_meta,
-# missRect=list(TRUE, TRUE),
-# type=list('Q', 'sqrt(Q)'),
-# info_header=TRUE,
-# time_header=NULL,
-# header_ratio=3,
-# figdir=figdir,
-# filename_opt='time')
-
-panel(list(res_QAtrend$data, res_QMNAtrend$data,
- res_VCN10trend$data),
- layout_matrix=c(1, 2, 3),
- df_meta=df_meta,
- df_trend=list(res_QAtrend$trend, res_QMNAtrend$trend,
+# panels_layout(list(df_data, df_data),
+# layout_matrix=c(1, 2),
+# df_meta=df_meta,
+# missRect=list(TRUE, TRUE),
+# type=list('Q', 'sqrt(Q)'),
+# info_header=TRUE,
+# time_header=NULL,
+# header_ratio=3,
+# figdir=figdir,
+# filename_opt='time')
+
+panels_layout(list(res_QAtrend$data, res_QMNAtrend$data,
+ res_VCN10trend$data),
+ layout_matrix=c(1, 2, 3),
+ df_meta=df_meta,
+ df_trend=list(res_QAtrend$trend, res_QMNAtrend$trend,
res_VCN10trend$trend),
- type=list(bquote(Q[A]), bquote(Q[MNA]), bquote(V[CN10])),
- missRect=list(TRUE, TRUE, TRUE),
- period=period,
- info_header=TRUE,
- time_header=df_data,
- header_ratio=2,
- figdir=figdir,
- filename_opt='')
+ type=list('Q[A]', 'Q[MNA]', 'V[CN10]'),
+ missRect=list(TRUE, TRUE, TRUE),
+ period=period,
+ info_header=TRUE,
+ time_header=df_data,
+ header_ratio=2,
+ figdir=figdir,
+ filename_opt='')
### /!\ Removed 185 row(s) containing missing values (geom_path) -> remove NA ###
--
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